Hi-AI

import { PromptDefinition, PromptResult } from '../../types/prompt.js'; export const codeConventionsDefinition: PromptDefinition = { name: 'code-conventions', description: 'Comprehensive code quality analysis and improvement using convention tools for standards validation, complexity analysis, and enhancement suggestions', arguments: [ { name: 'code_quality_task', description: 'Specific code quality task (validation, analysis, improvement, standards-check)', required: true }, { name: 'code_to_analyze', description: 'The code to analyze for quality and conventions', required: true }, { name: 'programming_language', description: 'Programming language of the code', required: true }, { name: 'quality_focus', description: 'Specific quality aspects to focus on (complexity, coupling, standards, improvements)', required: false }, { name: 'standards_level', description: 'Quality standards level (basic, intermediate, advanced, enterprise)', required: false } ] }; export function getCodeConventionsPrompt( codeQualityTask: string, codeToAnalyze: string, programmingLanguage: string, qualityFocus: string = 'comprehensive', standardsLevel: string = 'intermediate' ): PromptResult { return { messages: [ { role: 'user', content: { type: 'text', text: `Please perform comprehensive code quality analysis and improvement using all available code convention tools: **Code Quality Task:** ${codeQualityTask} **Programming Language:** ${programmingLanguage} **Quality Focus:** ${qualityFocus} **Standards Level:** ${standardsLevel} **Code to Analyze:** \`\`\`${programmingLanguage} ${codeToAnalyze} \`\`\` Use these specialized code convention tools for thorough quality assessment: ## Code Quality Analysis Process: ### 1. **Coding Standards Validation** (validate_code_quality) - Check adherence to language-specific coding standards - Validate naming conventions and code formatting - Assess documentation quality and completeness - Verify compliance with best practices ### 2. **Complexity Analysis** (analyze_complexity) - Measure cyclomatic complexity of functions and methods - Calculate cognitive complexity and maintainability metrics - Identify overly complex code that needs refactoring - Assess code readability and comprehension difficulty ### 3. **Coupling and Cohesion Assessment** (check_coupling_cohesion) - Analyze module coupling patterns and dependencies - Evaluate functional cohesion within modules - Identify tight coupling that reduces maintainability - Assess separation of concerns and modularity ### 4. **Quality Rules Application** (apply_quality_rules) - Apply comprehensive quality rule sets - Identify code smells and anti-patterns - Check for security vulnerabilities in code - Validate performance and efficiency patterns ### 5. **Improvement Suggestions** (suggest_improvements) - Generate specific, actionable improvement recommendations - Prioritize improvements by impact and effort - Provide refactoring suggestions with code examples - Recommend design pattern applications ### 6. **Coding Guide Reference** (get_coding_guide) - Reference language-specific coding guidelines - Compare code against established standards - Identify areas for standards improvement - Provide learning resources for quality enhancement ## Required Code Quality Output: **Standards Compliance Report:** - Adherence to coding standards and conventions - Formatting and style consistency assessment - Documentation quality evaluation - Best practices compliance check **Complexity Analysis:** - Cyclomatic and cognitive complexity metrics - Function complexity breakdown - Readability and maintainability scores - Refactoring recommendations for complex code **Coupling/Cohesion Assessment:** - Coupling type identification and severity - Cohesion level evaluation - Module dependency analysis - Modularity improvement suggestions **Quality Rules Results:** - Applied rule violations and severity levels - Code smell identification and categorization - Security vulnerability assessment - Performance issue detection **Improvement Recommendations:** - Prioritized list of specific improvements - Code examples for suggested changes - Effort estimation for each recommendation - Expected benefits and risk assessment **Standards Reference:** - Relevant coding guidelines and standards - Learning resources for improvement areas - Industry best practices alignment - Quality benchmark comparisons Provide comprehensive code quality analysis that enables systematic improvement of code standards, maintainability, and overall software quality.` } } ] }; }